Side-channel attacks allow extracting secret information from the execution
of cryptographic primitives by correlating the partially known computed data
and the measured side-channel signal. However, to set up a successful
side-channel attack, the attacker has to perform i) the challenging task of
locating the time instant in which the target cryptographic primitive is
executed inside a side-channel trace and then ii)the time-alignment of the
measured data on that time instant. This paper presents a novel deep-learning
technique to locate the time instant in which the target computed cryptographic
operations are executed in the side-channel trace. In contrast to
state-of-the-art solutions, the proposed methodology works even in the presence
of trace deformations obtained through random delay insertion techniques. We
validated our proposal through a successful attack against a variety of
unprotected and protected cryptographic primitives that have been executed on
an FPGA-implemented system-on-chip featuring a RISC-V CPU.

通过深度学习技术，本文提出了一种新颖的方法来定位侧信道迹线中执行目标计算密集型密码操作的时间点。与现有解决方案的区别在于，该方法能够在通过随机延迟插入技术获得的迹线变形的情况下正常工作。在实现了 RISC-V CPU 的 FPGA 系统上，通过成功攻击各种未受保护和受保护的密码原语进行了验证。